Studies related to the design of a magnetic suspension and balance system Interim technical report, Dec. 1964 - Jan. 1966

Magnetic suspension and balance system for use in hypersonic flow apparatu

Flight control systems properties and problems, volume 1

This volume contains a delineation of fundamental and mechanization-specific flight control characteristics and problems gleaned from many sources and spanning a period of over two decades. It is organized to present and discuss first some fundamental, generic problems of closed-loop flight control systems involving numerator characteristics (quadratic dipoles, non-minimum phase roots, and intentionally introduced zeros). Next the principal elements of the largely mechanical primary flight control system are reviewed with particular emphasis on the influence of nonlinearities. The characteristics and problems of augmentation (damping, stability, and feel) system mechanizations are then dealt with. The particular idiosyncracies of automatic control actuation and command augmentation schemes are stressed, because they constitute the major interfaces with the primary flight control system and an often highly variable vehicle response

Structural control interaction

The basic guidance and control concepts that lead to structural control interaction and structural dynamic loads are identified. Space vehicle ascent flight load sources and the load relieving mechanism are discussed, along with the the characteristics and special problems of both present and future space vehicles including launch vehicles, orbiting vehicles, and the Space Shuttle flyback vehicle. The special dynamics and control analyses and test problems apparent at this time are summarized

A novel approach to the control of quad-rotor helicopters using fuzzy-neural networks

Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotor’s ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications

On the Experimental Analysis of Integral Sliding Modes for Yaw Rate and Sideslip Control of an Electric Vehicle with Multiple Motors

With the advent of electric vehicles with multiple motors, the steady-state and transient cornering responses can be designed and implemented through the continuous torque control of the individual wheels, i.e., torque-vectoring or direct yaw moment control. The literature includes several papers on sliding mode control theory for torque-vectoring, but the experimental investigation is so far limited. More importantly, to the knowledge of the authors, the experimental comparison of direct yaw moment control based on sliding modes and typical controllers used for stability control in production vehicles is missing. This paper aims to reduce this gap by presenting and analyzing an integral sliding mode controller for concurrent yaw rate and sideslip control. A new driving mode, the Enhanced Sport mode, is proposed, inducing sustained high values of sideslip angle, which can be limited to a specified threshold. The system is experimentally assessed on a four-wheel-drive electric vehicle. The performance of the integral sliding mode controller is compared with that of a linear quadratic regulator during step steer tests. The results show that the integral sliding mode controller significantly enhances the tracking performance and yaw damping compared to the more conventional linear quadratic regulator based on an augmented singletrack vehicle model formulation. © 2018, The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Natur

Advances in Bio-Inspired Robots

This book covers three major topics, specifically Biomimetic Robot Design, Mechanical System Design from Bio-Inspiration, and Bio-Inspired Analysis on A Mechanical System. The Biomimetic Robot Design part introduces research on flexible jumping robots, snake robots, and small flying robots, while the Mechanical System Design from Bio-Inspiration part introduces Bioinspired Divide-and-Conquer Design Methodology, Modular Cable-Driven Human-Like Robotic Arm andWall-Climbing Robot. Finally, in the Bio-Inspired Analysis on A Mechanical System part, research contents on the control strategy of Surgical Assistant Robot, modeling of Underwater Thruster, and optimization of Humanoid Robot are introduced